something is off

Author: andrinr

examples/ansys/Readme.md

@@ -25,20 +25,21 @@ For the linux machine:
 Create a new python env. Assuming you using windows powerhsell, install the required dependencies:
 
 ```bash
-pip install tesseract-core[runtime]
+pip install tesseract-core[runtime] trimesh
 ```
 
 Clone this repository, navigate to the `examples/ansys/spaceclaim_tess` directory and start the Tesseract runtime server with:
 
 ```bash
-tesseract-runtime serve --port <port_number_1>
+tesseract-runtime serve --port <port_number_1> --host 0.0.0.0
 ```
 Note that we dont build a Tesseract image for SpaceClaim in this example. This is because SpaceClaim cannot be installed in a containerized environment. You can test it using git bash and your specific Spaceclaim.exe Path:
 
 ```bash
-curl -d '{"inputs":{"differentiable_bar_parameters": [[0, 3.14], [0.39, 3.53], [0.79, 3.93], [1.18, 4.32], [1.57, 4.71], [1.96, 5.11], [2.36, 5.50], [2.75, 5.89]], "differentiable_plane_parameters": [200, 600], "non_differentiable_parameters": [800, 100], "string_parameters":["F:\\Ansys installations\\ANSYS Inc\\v241\\scdm\\SpaceClaim.exe", "geometry_generation.scscript"]}}' -H "Content-Type: application/json" http://127.0.0.1:8000/apply
+curl -d '{"inputs":{"differentiable_bar_parameters": [[0, 3.14], [0.39, 3.53], [0.79, 3.93], [1.18, 4.32], [1.57, 4.71], [1.96, 5.11], [2.36, 5.50], [2.75, 5.89]], "differentiable_plane_parameters": [200, 600], "non_differentiable_parameters": [800, 100], "string_parameters":["F:\\ANSYS Inc\\v242\\scdm\\SpaceClaim.exe", "geometry_generation.scscript"]}}' -H "Content-Type: application/json" http://172.26.3.35:443/apply
 ```
 
+
 or the equivalent on powershell:
 
 ```powershell

examples/ansys/fem_shapeopt_mesh.vtk

@@ -117,7 +117,6 @@ def stress(u_grad, theta):
             lmbda = E * nu / ((1 + nu) * (1 - 2 * nu))
 
             epsilon = 0.5 * (u_grad + u_grad.T)
-            sigma = lmbda * jnp.trace(epsilon) * jnp.eye(self.dim) + 2 * mu * epsilon
 
             sigma = lmbda * jnp.trace(epsilon) * jnp.eye(self.dim) + 2.0 * mu * epsilon
             return sigma
@@ -141,6 +140,7 @@ def set_params(self, params: jnp.ndarray) -> None:
         # Override base class method.
         full_params = jnp.ones((self.fe.num_cells, params.shape[1]))
         full_params = full_params.at[self.fe.flex_inds].set(params)
+        print(self.fe.num_quads)
         thetas = jnp.repeat(full_params[:, None, :], self.fe.num_quads, axis=1)
         self.full_params = full_params
         self.internal_vars = [thetas]
@@ -209,6 +209,7 @@ def bc_factory(
             # Create a factory that captures the current value of i
             def make_location_fn(idx):
                 def location_fn(point, index):
+                    # jax.debug.print("Mask at point {}: {}", point, jax.lax.dynamic_index_in_dim(masks, index, 0, keepdims=False))
                     return (
                         jax.lax.dynamic_index_in_dim(masks, index, 0, keepdims=False)
                         == idx
@@ -218,12 +219,18 @@ def location_fn(point, index):
 
             def make_value_fn(idx):
                 def value_fn(point):
+                    # jax.debug.print("Value {} at point {}", jax.lax.dynamic_index_in_dim(values, idx, 0, keepdims=False), point)
                     return values[idx]
 
                 return value_fn
 
             def make_value_fn_vn(idx):
                 def value_fn_vn(u, x):
+                    jax.debug.print(
+                        "Van Neumann Value {} at point {}",
+                        jax.lax.dynamic_index_in_dim(values, idx, 0, keepdims=False),
+                        x,
+                    )
                     return values[idx]
 
                 return value_fn_vn
@@ -238,6 +245,9 @@ def value_fn_vn(u, x):
     dirichlet_values = jnp.array(dirichlet_values)
     van_neumann_values = jnp.array(van_neumann_values)
 
+    print(f"dirichlet_values: {dirichlet_values}")
+    print(f"van_neumann_values: {van_neumann_values}")
+
     dirichlet_location_fns, dirichlet_value_fns = bc_factory(
         dirichlet_mask, dirichlet_values
     )
@@ -281,40 +291,6 @@ def apply_fn(inputs: dict) -> dict:
     Returns:
         Dictionary containing the compliance of the structure.
     """
-    from typing import TypeVar
-
-    T = TypeVar("T")
-
-    def stop_grads_int(x: T) -> T:
-        """Stops gradient computation.
-
-        We cannot use jax.lax.stop_gradient directly because Tesseract meshes are
-        nested dictionaries with arrays and integers, and jax.lax.stop_gradient
-        does not support integers.
-
-        Args:
-                x: Input value.
-
-        Returns:
-                Value with stopped gradients.
-        """
-
-        def stop(x):
-            return jax._src.ad_util.stop_gradient_p.bind(x)
-
-        return jax.tree_util.tree_map(stop, x)
-
-    # stop grads on all inputs except rho
-
-    # problem, fwd_pred = setup(
-    #     pts=stop_grads_int(inputs["hex_mesh"]["points"][: inputs["hex_mesh"]["n_points"]]),
-    #     cells=stop_grads_int(inputs["hex_mesh"]["faces"][: inputs["hex_mesh"]["n_faces"]]),
-    #     dirichlet_mask=stop_grads_int(inputs["dirichlet_mask"]),
-    #     dirichlet_values=stop_grads_int(inputs["dirichlet_values"]),
-    #     van_neumann_mask=stop_grads_int(inputs["van_neumann_mask"]),
-    #     van_neumann_values=stop_grads_int(inputs["van_neumann_values"]),
-    # )
-
     # no stop grads
     problem, fwd_pred = setup(
         pts=inputs["hex_mesh"]["points"][: inputs["hex_mesh"]["n_points"]],

examples/ansys/fem_tess/tesseract_api.py

@@ -2,8 +2,9 @@
 
 images = []
 
-for i in range(30):
+for i in range(60):
     filename = f"tmp_img/mesh_optim_{i:03d}.png"
     images.append(imageio.imread(filename))
     print(f"Added {filename} to gif.")
-imageio.mimsave("mesh_optim.gif", images, fps=10)
+# make sure the gif repeats forever
+imageio.mimsave("mesh_optim.gif", images, fps=10, loop=0)

examples/ansys/gf.py

@@ -84,13 +84,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 342,
+   "execution_count": null,
    "id": "8a407fb1",
    "metadata": {},
    "outputs": [],
    "source": [
     "# design_tess = Tesseract.from_image(\"design-tube-sdf\")\n",
     "# design_tess.serve()\n",
+    "IP = \"172.26.3.35\"\n",
     "design_tess = Tesseract.from_tesseract_api(\"hot_design_tess/tesseract_api.py\")\n",
     "bar_3d_tess = Tesseract.from_tesseract_api(\"bars_3d_tess/tesseract_api.py\")"
    ]